cmip6 historical ice area data

[phaustin]

1. Phil will move Shuting's precip notebooks into the website and find the seaice variable for one of the historical runs

[phaustin]

For week of Feb 3:

1. Phil will make the BCC precip notebook work on jupyterhub-2
2. Alison will find two models -- Canadian model and the British model
3. Phil/Alison will plot sic and snt in polar sterographic coords using cartopy

[adeere]

2

• Canadian Model: CCCma - Canadian Centre for Climate Modelling and Analysis
• British Model: Not sure which one?
  • ECMWF - European Centre for Medium-Range Weather Forecasts (Reading) -> HighResMIP
  • MOHC - Met Office Hadley Centre, Exeter -> seemingly CMIP
  • NERC - Natural Environmental Research Council, Oxford
• in SImon (monthly sea-ice data) there is the variable sithick which is the sea-ice thickness and could be helpful or siconc (sea-ice area percentage on an ocean grid) or siconca (sea-ice area percentage on an atmospheric grid)

[phaustin]

great site for cmip6 data/plotting: https://nordicesmhub.github.io/NEGI-Abisko-2019/training/CMIP6_example.html https://unidata.github.io/MetPy/latest/tutorials/declarative_tutorial.html#sphx-glr-tutorials-declarative-tutorial-py

[phaustin]

phil: -- I'll make sure pandas 4 part lesson is working. I'll download ice concentration satellite data. alison: -- will make polar plot of sea ice for hadley and cccma historical run snapshot research question -- model comparison, model vs. data, we just a metric.

[adeere]

research question vague start:

• How do the Canadian (CCCma) and British (MOHC) models differ from each other and from near-real-time gridded sea ice in the Arctic, does one model better match satellite satellite data?
  • Should this include a time range?
  • For comparing sea ice, should I look at thickness? Or a different variable?
  • Should this include statistics that I will use?
  • definitely needs to be more specific!